Enhanced Fingerprint Miniature Extraction and Matching Algorithms for Automated Teller Machines (ATMs)

Abstract - The purpose of the study was to design, implement and enhance the security features of Automated Teller Machines (ATMs) in Namibian perspective. In this study, fingerprint data and PIN number details were combined in order to improve the security of the ATM system. The fingerprint miniature extraction algorithms as well as fingerprint matching algorithms were used in this study. The sample of fingerprints used in this research were obtained from FVC 2000, FVC 2002 and FVC 2004 databases. The programming language used to develop and improve the fingerprint extraction and matching algorithm was C#. The proposed mechanism showed better results as compared to the existing ATM security systems. The false rejection rate (FRR) as well as the false acceptance rate (FAR), were significantly reduced. The average delay to complete the transaction at an ATM using the proposed mechanism was slightly increased due to the augmented security. However, in the Namibian context, the delay is not a major concern as compared to the security that would have been improved